D

deep learning

This is an implementation of a very simple neural network from scratch.

This project provides a deep learning approach to learn machining features from CAD models using a hierarchical graph convolutional neural network.

Protocol for network and expression integration to identify potential defense gene in host-pathogen interactions

Projet personnel de classification des maladies des feuilles d'arbre. Article technique disponible sur mon blog : https://boulayc.gitlab.io/blog/

PDE-based Group Equivariant CNNs for PyTorch

FakET: Simulating Cryo-Electron Tomograms with Neural Style Transfer

Webpage for the L52+ lab

Benchmarking framework for machine learning with fNIRS

https://doi.org/10.3389/fnrgo.2023.994969

This is the unpaired image-2-image and volume-2-volume translation project. It converts images or volumes of an input domain to a target domain using artificial intelligence.

This is a project to train, use and analyze 2D and 3D neural networks for segmentation.

Lifelong learning is a complex topic in machine learning, whether in combination with reinforce- ment learning or other learning methods. There are different approaches for this and one of them are hypernetworks. Hypernetworks have the advantage of having a very large ability to preserve past memories. Recent work attempts to demonstrate the learning ability of multiple tasks with a hypernetwork such as in the combination of reinforcement learning.

Research, code, algorithms and all related to artificial intelligence

Company Ticker Predictor s designed to leverage deep learning for more accurate predictions of company ticker prices. This system uses a multi-layered LSTM model to capture temporal dependencies in historical data, making it particularly effective in handling sequential data and ticker market volatility. The entire prediction pipeline is integrated and deployed using Streamlit.

A tool to annotate radiology images.

Darknet got illuminated by PyTorch ~ Meet Lightnet

This is a project to train, use and analyze 2D and 3D neural networks for segmentation. It contains a UI and is implemented in pytorch and django as backend.

Yolov5-segmentation identity card detection and rotation with the NCNN and OpenCV framework.

This project is a re-implementation of FeatureNet using Tensorflow 2. With working segmentation code.